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markhenry
/
vanilla-v5

PyTorch
language-model
gpt
Model card Files
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vanilla-v5
File size: 2,130 Bytes
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{
  "data_dir": "../data/fineweb-edu-10B",
  "batch_size": 80,
  "seq_len": 1024,
  "max_iters": 16000,
  "gradient_accumulation_steps": 1,
  "optimizer": "muon",
  "learning_rate": 0.0006,
  "min_lr": 6e-05,
  "weight_decay": 0.1,
  "beta1": 0.9,
  "beta2": 0.95,
  "grad_clip": 1.0,
  "warmup_iters": 0,
  "lr_decay_iters": 16000,
  "muon_lr": 0.01,
  "muon_min_lr": 0.002,
  "adamw_lr": 0.01,
  "adamw_min_lr": 0.00036,
  "muon_momentum": 0.95,
  "muon_nesterov": true,
  "muon_ns_steps": 5,
  "muon_weight_decay": 0.0,
  "lr_schedule": "linear_warmdown",
  "warmdown_frac": 0.4,
  "device": "cuda",
  "dtype": "bfloat16",
  "compile": true,
  "sequential_data": false,
  "n_layer": 12,
  "n_head": 8,
  "n_embd": 1024,
  "block_size": 1024,
  "vocab_size": 50304,
  "sparsity_mode": "none",
  "k1": 8,
  "k2": 64,
  "m2": null,
  "basis_k": 128,
  "r": 32,
  "hash_seed": 42,
  "deeptopk_backend": "auto",
  "rmsnorm_affine": true,
  "wf_f_min_ratio": 0.0,
  "wf_quantile_lr": 0.1,
  "wf_ema_beta": 0.9,
  "weight_sparsify": false,
  "weight_sparsify_k": 32,
  "grad_sparsify_k": 4,
  "l1l1_grad_proj": false,
  "sgd_lr": 0.01,
  "sgd_min_lr": 0.001,
  "sgd_momentum": 0.9,
  "sgd_weight_decay": 0.0,
  "cayley_levels": [],
  "cayley_per_parent_budget": false,
  "cayley_wf_f_min_ratio": 0.0,
  "cayley_wf_ema_beta": 0.99,
  "cayley_wf_bisect_iters": 15,
  "cayley_wf_warmup_batches": 10,
  "cayley_wf_batch_size": 64,
  "cayley_seed": 42,
  "cayley_backend": "auto",
  "cayley_locations": [
    "resid_mid"
  ],
  "cayley_score_standardize": false,
  "cayley_richardson_refine": false,
  "cayley_matching_pursuit": false,
  "cayley_sparse_mlp": false,
  "sparse_mlp_fan_out": 64,
  "sparse_mlp_K_out": 0,
  "sparse_mlp_activation": "relu",
  "sparse_mlp_chunk_size": 1024,
  "sparse_mlp_norm_preserve": true,
  "sparse_mlp_backend": "auto",
  "sparse_mlp_target_hidden_size": 4,
  "tied_block_init": false,
  "dead_threshold_c": 0.1,
  "resume": false,
  "out_dir": "../out/vanilla-v5",
  "eval_interval": 500,
  "eval_iters": 100,
  "log_interval": 10,
  "wandb_project": "sparse-nanogpt",
  "wandb_run_name": "vanilla-v5"
}